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Misc cleanups from exploring Clang warnings
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@ -51,10 +51,10 @@ namespace Catch {
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private:
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private:
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// If this is a constructor benchmark, destruct the underlying object
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// If this is a constructor benchmark, destruct the underlying object
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template <typename U>
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template <typename U>
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void destruct_on_exit(std::enable_if_t<Destruct, U>* = 0) { destruct<true>(); }
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void destruct_on_exit(std::enable_if_t<Destruct, U>* = nullptr) { destruct<true>(); }
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// Otherwise, don't
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// Otherwise, don't
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template <typename U>
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template <typename U>
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void destruct_on_exit(std::enable_if_t<!Destruct, U>* = 0) { }
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void destruct_on_exit(std::enable_if_t<!Destruct, U>* = nullptr) { }
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T& stored_object() {
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T& stored_object() {
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return *static_cast<T*>(static_cast<void*>(&data));
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return *static_cast<T*>(static_cast<void*>(&data));
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@ -54,7 +54,7 @@ namespace Catch {
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double mean(Iterator first, Iterator last) {
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double mean(Iterator first, Iterator last) {
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auto count = last - first;
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auto count = last - first;
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double sum = std::accumulate(first, last, 0.);
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double sum = std::accumulate(first, last, 0.);
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return sum / count;
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return sum / static_cast<double>(count);
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}
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}
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template <typename Estimator, typename Iterator>
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template <typename Estimator, typename Iterator>
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@ -100,7 +100,7 @@ namespace Catch {
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});
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});
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double accel = sum_cubes / (6 * std::pow(sum_squares, 1.5));
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double accel = sum_cubes / (6 * std::pow(sum_squares, 1.5));
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int n = static_cast<int>(resample.size());
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long n = static_cast<long>(resample.size());
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double prob_n = std::count_if(resample.begin(), resample.end(), [point](double x) { return x < point; }) / static_cast<double>(n);
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double prob_n = std::count_if(resample.begin(), resample.end(), [point](double x) { return x < point; }) / static_cast<double>(n);
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// degenerate case with uniform samples
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// degenerate case with uniform samples
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if (prob_n == 0) return { point, point, point, confidence_level };
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if (prob_n == 0) return { point, point, point, confidence_level };
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@ -108,7 +108,7 @@ namespace Catch {
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double bias = normal_quantile(prob_n);
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double bias = normal_quantile(prob_n);
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double z1 = normal_quantile((1. - confidence_level) / 2.);
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double z1 = normal_quantile((1. - confidence_level) / 2.);
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auto cumn = [n]( double x ) -> int {
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auto cumn = [n]( double x ) -> long {
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return std::lround( normal_cdf( x ) * n );
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return std::lround( normal_cdf( x ) * n );
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};
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};
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auto a = [bias, accel](double b) { return bias + b / (1. - accel * b); };
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auto a = [bias, accel](double b) { return bias + b / (1. - accel * b); };
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@ -116,7 +116,7 @@ namespace Catch {
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double b2 = bias - z1;
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double b2 = bias - z1;
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double a1 = a(b1);
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double a1 = a(b1);
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double a2 = a(b2);
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double a2 = a(b2);
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auto lo = static_cast<size_t>((std::max)(cumn(a1), 0));
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auto lo = static_cast<size_t>((std::max)(cumn(a1), 0l));
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auto hi = static_cast<size_t>((std::min)(cumn(a2), n - 1));
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auto hi = static_cast<size_t>((std::min)(cumn(a2), n - 1));
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return { point, resample[lo], resample[hi], confidence_level };
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return { point, resample[lo], resample[hi], confidence_level };
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